AI Agent Development
AI agent development becomes useful when an agent does more than answer: it uses sources, tools, rules, and approvals to complete a task.
Product systems and software architectures with Google Agent Development Kit (ADK), React Native & React
A support advisor workspace helps teams handle customer history, knowledge sources, response drafts, risks, and escalations in one surface.
This workspace helps support teams understand tickets faster, find the right sources, and prepare replies under control.
Support gets a workspace with ticket, history, product state, sources, reply draft, and escalation path.
appamass connects the web workspace, TypeScript contracts, and Agent Development Kit (ADK)-based agents so drafts show sources and people stay responsible for the answer.
The first build should cover one common ticket type and show where the draft is solid, uncertain, or should be escalated.
Support becomes faster when context is already organized. The team still needs to see which source supports an answer and when a case should escalate.
Users see ticket context, previous contacts, relevant articles, draft response, risk hints, and escalation option.
CRM or ticket APIs, knowledge base, retrieval, Agent Development Kit (ADK) tools, response generation, React/Vite review surface, roles, and logging connect behind the workspace.
Customer data, source access, response suggestions, tone, escalation rules, audit trail, and privacy stay controlled.
The first build should support a common ticket type while reducing response time and keeping quality traceable.
Ticket, history, product status, and relevant sources are combined in one view.
The draft shows reasoning, sources, uncertainty, and editable parts.
Risk, priority, owner, and next step are clearly marked.
Related areas showing how mobile apps, React web systems, AI agents, and controllable automations fit together.